Beautoklavio Putbetonio Šiluminių Techninių Savybių Tyrimai

Gnip, Ivan; Keršulis, V.; Laukaitis, A.

doi:10.1080/13921525.1996.10590173

Cited by 6 publications

(16 citation statements)

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“…An example of this model is the pricing model of Gnip [4]. Similar to the previous case, only basic unit prices can be described.…”

Section: A Prototypementioning

confidence: 99%

“…They often support operations to work on data assets collectively, instead of individual data assets, and hence service information focuses on describing service as a whole and service APIs. Examples include Gnip [4] and networks of bio-diversity data assets.…”

Section: A Types Of Daasmentioning

confidence: 99%

“…Since the last couple of years we have witnessed the rapid growth in the number of DaaSes. Typical DaaS providers support from generic data assets, such as Amazon [1], Microsoft Azure Data Marketplace [2] and Infochimps [3], to specific data assets, like Gnip [4].…”

Section: Introductionmentioning

confidence: 99%

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DEMODS: A Description Model for Data-as-a-Service

Pham

Truong

et al. 2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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“…An example of this model is the pricing model of Gnip [4]. Similar to the previous case, only basic unit prices can be described.…”

Section: A Prototypementioning

confidence: 99%

Section: A Types Of Daasmentioning

confidence: 99%

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DEMODS: A Description Model for Data-as-a-Service

Pham

Truong

et al. 2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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“…They do so for two main reasons: recent data are generally more interesting to users, and many microblog service providers consider selling access to historic data an important monetization channel [1,2].…”

Section: Problem Definitionmentioning

confidence: 99%

“…Thus, a a sociologist will never be able to study the origin of a trending keyword unless he/she is somehow (magically) able to predict such a keyword ahead of time. Note that there are companies like GNIP [2] and Datasift [1] that sell historic microblog data; however the subscription fee is often rather high (e.g., $3,000 per month for Twitter alone at Datasift.com [1]) for a non-commercial setting such as social science research.…”

Section: Introductionmentioning

confidence: 99%

Aggregate estimation over a microblog platform

Thirumuruganathan

Zhang

Hristidis

et al. 2014

Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data

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Microblogging platforms such as Twitter have experienced a phenomenal growth of popularity in recent years, making them attractive platforms for research in diverse fields from computer science to sociology. However, most microblogging platforms impose strict access restrictions (e.g., API rate limits) that prevent scientists with limited resources -e.g., who cannot afford microblog-data-access subscriptions offered by GNIP et al. -to leverage the wealth of microblogs for analytics. For example, Twitter allows only 180 queries per 15 minutes, and its search API only returns tweets posted within the last week. In this paper, we consider a novel problem of estimating aggregate queries over microblogs, e.g., "how many users mentioned the word 'privacy' in 2013?". We propose novel solutions exploiting the user-timeline information that is publicly available in most microblogging platforms. Theoretical analysis and extensive real-world experiments over Twitter, Google+ and Tumblr confirm the effectiveness of our proposed techniques.

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HIV Cure Goes Viral: An Analysis of HIV Cure #Hashtags from Twitter Around the Mississippi Baby Announcement (Preprint)

Gilbertson¹

2017

Preprint

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Background: On 3 March 2013, an announcement was made concerning the possible functional HIV cure of the "Mississippi baby" at the Conference on Retroviruses and Opportunistic Infections (CROI) in Atlanta, Georgia, USA. Immediately following this announcement, word spread across traditional media outlets, and social media platforms such as Twitter, rousing tremendous public excitement.Objective: The purpose of this study was to examine the frequency, content, and sentiment of HIV cure-related messages (tweets/retweets) on Twitter around the HIV "cure" Mississippi baby announcement on the 3 of March 2013.Methods: We obtained a dataset containing all HIV cure messages between 13 January and 16 May 2013 and conducted qualitative analyses on a 1,111-message sample.Results: A sharp increase (2,786%) in HIV cure-related messages occurred immediately following the announcement. However, this sharp increase only lasted approximately 19 days. Out of our sample of 1,111 messages most were from individuals (68.1%) or news organizations (18.3%), including the single most retweeted post from the BBC (20,047 retweets). 36.6% of these messages were coded as opinion/commentary and 26.7% were coded as news. The proportion of messages with neutral sentiment increased (42.5% to 53.9%; P = 0.003 while the proportion of those with negative sentiment decreased (15.6% to 9.2%; P = 0.01.Conclusions: The Mississippi baby announcement substantially increased HIV curerelated social media messages. Tweets from individuals dominated this platform; messages from public health agencies were relatively under-represented. The increased public attention garnered after the announcement was short-lived. Similar surges in public attention following future HIV cure breakthrough announcements may offer opportunities to reduce negative perceptions of HIV and improve community engagement.

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Beautoklavio Putbetonio Šiluminių Techninių Savybių Tyrimai

Cited by 6 publications

References 0 publications

DEMODS: A Description Model for Data-as-a-Service

DEMODS: A Description Model for Data-as-a-Service

Aggregate estimation over a microblog platform

HIV Cure Goes Viral: An Analysis of HIV Cure #Hashtags from Twitter Around the Mississippi Baby Announcement (Preprint)

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